Metabarcoding to monitor the crustacean zooplankton of a lake improves when using a reference DNA library from local samples

Di Dieter Ebert, Basel, Switzerland - Opera propria, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=47025870
Submitted: 7 July 2022
Accepted: 16 January 2023
Published: 8 February 2023
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Biodiversity surveys through morphology provide invaluable data to inform biological monitoring efforts, involving specialised taxonomic skills that are not always available. The revolution brought by the advent of metabarcoding associated to massive sequencing is currently seen as a potential advance, even if different approaches may often provide different results. Here we test if reliable results from metabarcoding can be obtained by i) basing the analyses on a detailed knowledge of the local diversity from morphology, ii) applying tools from DNA taxonomy to create a local reference library, ii) developing custom primers, taking as example the crustacean zooplankton of a subalpine lake in Northern Italy, Lake Maggiore. We support the idea that occurrences from metabarcoding can be reliable, especially with targeted primers, but we confirm that read numbers from massive sequencing could not be related to abundance of individuals in our analyses. Data from metabarcoding can thus be used to reliably monitor species occurrence in the lake, but not changes in abundance.

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Adamowicz SJ, 2015. International Barcode of Life: Evolution of a global research community. Genome 58:151-162. DOI: https://doi.org/10.1139/gen-2015-0094
Arfè A, Quatto P, Zambon A, MacIsaac HJ, Manca M, 2019. Long-term changes in the zooplankton community of Lake Maggiore in response to multiple stressors: A functional principal components analysis. Water 11:962. DOI: https://doi.org/10.3390/w11050962
Baird DJ, Hajibabaei M, 2012. Biomonitoring 2.0: a new paradigm in ecosystem assessment made possible by next‐generation DNA sequencing. Mol Ecol 21:2039-2044. DOI: https://doi.org/10.1111/j.1365-294X.2012.05519.x
Bergsten J, Bilton DT, Fujisawa T, Elliott M, Monaghan MT, Balke M, et al., 2012. The effect of geographical scale of sampling on DNA barcoding. Syst Biol 61:851-869. DOI: https://doi.org/10.1093/sysbio/sys037
Bik HM, 2021. Just keep it simple? Benchmarking the accuracy of taxonomy assignment software in metabarcoding studies. Mol Eco Ress 21:2187-2189. DOI: https://doi.org/10.1111/1755-0998.13473
Birk S, Bonne W, Borja A, Brucet S, Courrat A, Poikane S, et al., 2012. Three hundred ways to assess Europe's surface waters: an almost complete overview of biological methods to implement the Water Framework Directive. Ecol Indic 18:31-41. DOI: https://doi.org/10.1016/j.ecolind.2011.10.009
Borgmann U, Shear H, Moore J, 1984. Zooplankton and potential fish production in Lake Ontario. Can J Fish Aquat Sci 41:1303-1309. DOI: https://doi.org/10.1139/f84-159
Bucklin A, Peijnenburg KT, Kosobokova KN, O’Brien TD, Blanco-Bercial L, Cornils A, et al., 2021. Toward a global reference database of COI barcodes for marine zooplankton. Mar Biol 168:1-26. DOI: https://doi.org/10.1007/s00227-021-03887-y
Burki F, Sandin MM, Jamy M, 2021. Diversity and ecology of protists revealed by metabarcoding. Curr Biol 31:R1267-R1280. DOI: https://doi.org/10.1016/j.cub.2021.07.066
Carney HJ, Elser JJ, 1990. Strength of zooplankton-phytoplankton coupling in relation to lake trophic state, p. 615-631. In: Tilzer MM, Serruya C (eds), Large Lakes. Brock/Springer Series in Contemporary Bioscience. Springer. DOI: https://doi.org/10.1007/978-3-642-84077-7_33
Chain FJJ, Brown EA, MacIsaac HJ, Cristescu ME, 2016. Metabarcoding reveals strong spatial structure and temporal turnover of zooplankton communities among marine and freshwater ports. Divers Distrib 22:493-504. DOI: https://doi.org/10.1111/ddi.12427
Collins RA, Cruickshank RH, 2013. The seven deadly sins of DNA barcoding. Mol Ecol Res 13:969-975. DOI: https://doi.org/10.1111/1755-0998.12046
de Bernardi R, Giussani G, Manca M, Ruggiu D, 1988. Long-term dynamics of plankton communities in Lago Maggiore (N. Italy). Int Ver Theor Angew Limnol Verhand 23:729-733. DOI: https://doi.org/10.1080/03680770.1987.11899700
Dussart B, 1969. Les Copépodes des Eaux continentales d'Europe occidentale. Tome II: Cyclopoides et Biologie. Paris: Editions N. Boublée and Cie; 292 pp.
Edgar RC, 2016. UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing. bioRxiv 081257. DOI: https://doi.org/10.1101/081257
Edgar RC, 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Meth 10:996. DOI: https://doi.org/10.1038/nmeth.2604
Einsle U, 1993. Crustacea: Copepoda: Calanoida und Cyclopoida. Subwasserfauna bon Mitteleuropa. Bd. 8/Heft 4/Teil 1. Gustav Fischer Verlag, Stuttgart: 209 pp.
Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R, 1994. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotechnol 3:294-299.
Fonseca VG, 2018. Pitfalls in relative abundance estimation using eDNA metabarcoding. Mol Ecol Res 18:923-926. DOI: https://doi.org/10.1111/1755-0998.12902
Geiger MF, Astrin JJ, Borsch T, Burkhardt U, Grobe P, Hand R, et al., 2016. How to tackle the molecular species inventory for an industrialized nation—lessons from the first phase of the German Barcode of Life initiative GBOL (2012–2015). Genome 59:661-670. DOI: https://doi.org/10.1139/gen-2015-0185
Giussani G, de Bernardi R, Ruffoni T, 1990. Three years of experience in biomanipulating a small eutrophic lake: Lago di Candia (Northern Italy). Hydrobiologia 200:357-366. DOI: https://doi.org/10.1007/978-94-017-0924-8_30
Gómez A, Serra M, Carvalho GR, Lunt DH, 2002. Speciation in ancient cryptic species complexes: Evidence from the molecular phylogeny of Brachionus plicatilis (Rotifera). Evolution 56:1431–1444. DOI: https://doi.org/10.1111/j.0014-3820.2002.tb01455.x
Griebel J, Gießler S, Poxleitner M, Navas Faria A, Yin M, Wolinska J, 2015. Extreme environments facilitate hybrid superiority – The story of a successful Daphnia galeata × longispina hybrid clone. PloS One 10:e0140275. DOI: https://doi.org/10.1371/journal.pone.0140275
Guindon S, Dufayard J, Lefort V, Anisimova M, Hordijk W, Gascuel O, 2010. New algorithms and methods to estimate Maximum-Likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 59:307-321. DOI: https://doi.org/10.1093/sysbio/syq010
Hamza W, Ruggiu D, Manca M, 1993. Diel zooplankton migrations and their effect on the grazing impact in Lake Candia (Italy). In: Ringelberg J (ed), Proceedings Symposium “Diel vertical migration of zooplankton”. Ergeb Limnol 39:175-185.
Hobæk A, Skage M, Schwenk K, 2004. Daphnia galeata × D. longispina hybrids in western Norway. Hydrobiologia 526:55-62. DOI: https://doi.org/10.1023/B:HYDR.0000041614.68315.ec
Jeppesen E, Noges P, Davidson TA, Haberman J, Noges T, Blank K, et al., 2011. Zooplankton as indicators in lakes: a scientific-based plea for including zooplankton in the ecological quality assessment of lakes according to the European Water Framework Directive (WFD). Hydrobiologia 676:279-297. DOI: https://doi.org/10.1007/s10750-011-0831-0
Kallis G, Butler D, 2001. The EU water framework directive: measures and implications. Water Policy 3:125-142. DOI: https://doi.org/10.1016/S1366-7017(01)00007-1
Kiemel K, Weithoff G, Tiedemann R, 2022. DNA metabarcoding reveals impact of local recruitment, dispersal, and hydroperiod on assembly of a zooplankton metacommunity. Mol Ecol online ahead of print. DOI: https://doi.org/10.22541/au.164374406.69936636/v1
Kiefer F, 1968. Versuch einer Revision der Gattung Eudiaptomus Kiefer (Copepoda, Calanoida). Mem Ist Ital Idrobiol 24:9-160.
Kiefer F, 1978. Freilebend Copepoda – Die Binnengewässer. vol 26. Stuttgart: Schweizerbart’sche Verlagsbuchhandlung; 343 pp.
Krehenwinkel H, Wolf M, Lim JY, Rominger AJ, Simison WB, Gillespie RG, 2017. Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding. Sci Rep 7:1-12. DOI: https://doi.org/10.1038/s41598-017-17333-x
Kuraku S, Zmasek CM, Nishimura O, Katoh K, 2013. aLeaves facilitates on-demand exploration of metazoan gene family trees on MAFFT sequence alignment server with enhanced interactivity. Nucleic Acids Re 41:22-28. DOI: https://doi.org/10.1093/nar/gkt389
Lamb PD, Hunter E, Pinnegar JK, Creer S, Davies RG, Taylor MI, 2019. How quantitative is metabarcoding: A meta-analytical approach. Mol Ecol 28:420-430. DOI: https://doi.org/10.1111/mec.14920
Leb C, 2015. One step at a time: international law and the duty to cooperate in the management of shared water resources. Water Int 40:21-32. DOI: https://doi.org/10.1080/02508060.2014.978972
Leese F, Altermatt F, Bouchez A, Ekrem T, Hering D, Meissner K, et al., 2016. DNAqua-Net: Developing new genetic tools for bioassessment and monitoring of aquatic ecosystems in Europe. Res Ideas Outcomes 2:e11321.
Lepori F, 2020. Breve storia dello zooplancton da crostacei della zona pelagica del Lago di Lugano. Bollettino Società Ticinese Scienze Naturali 108:97-102.
Leray M, Knowlton N, 2017. Random sampling causes the low reproducibility of rare eukaryotic OTUs in Illumina COI metabarcoding. PeerJ 5:e3006. DOI: https://doi.org/10.7717/peerj.3006
Leray M, Yang JY, Meyer CP, Mills SC, Agudelo N, Ranwez V, Boehm JT, Machida RJ, 2013. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front Zool 10:34. DOI: https://doi.org/10.1186/1742-9994-10-34
Lim NKM, Tay YC, Srivathsan A, Tan JWT, Kwik JTB, Baloğlu B, Meier R, Yeo DCJ, 2016. Next-generation freshwater bioassessment: eDNA metabarcoding with a conserved metazoan primer reveals species-rich and reservoir-specific communities. Roy Soc Open Sci 3:160635. DOI: https://doi.org/10.1098/rsos.160635
Lindenmayer DB, Likens GE, 2009. Adaptive monitoring: a new paradigm for long-term research and monitoring. Trends Ecol Evol 24:482-486. DOI: https://doi.org/10.1016/j.tree.2009.03.005
Lucentini L, Rebora M, Puletti ME, Gigliarelli L, Fontaneto D, Gaino E, Panara F, 2011. Geographical and seasonal evidence of cryptic diversity in the Baetis rhodani complex (Ephemeroptera, Baetidae) revealed by means of DNA taxonomy. Hydrobiologia 673:215-228. DOI: https://doi.org/10.1007/s10750-011-0778-1
Lüdecke D, Ben-Shachar MS, Patil I, Waggoner P, Makowski D, 2021. performance: An R Package for Assessment, Comparison and Testing of Statistical Models. J Open Source Softw 6:3139. DOI: https://doi.org/10.21105/joss.03139
Maddison W, Maddison D, 2008. Mesquite 2. A modular system for evolutionary analysis. Available from: http://www.mesquiteproject.org
Magoga G, Fontaneto D, Montagna M, 2021. Factors affecting the efficiency of molecular species delimitation in a species‐rich insect family. Mol Ecol Res 21:1475-1489. DOI: https://doi.org/10.1111/1755-0998.13352
Magurran AE, Baillie SR, Buckland ST, Dick JMP, Elston DA, Scott EM, Smith RI, Somerfield PJ, Watt AD, 2010. Long-term datasets in biodiversity research and monitoring: Assessing change in ecological communities through time. Trends Ecol Evol 25:574-582. DOI: https://doi.org/10.1016/j.tree.2010.06.016
Manca M, Cavicchioni N, Morabito G, 2000. First observations on the effect of a complete, exceptional overturn of Lake Maggiore on plankton and primary productivity. Int Rev Hydrobiol 85:209-222. DOI: https://doi.org/10.1002/(SICI)1522-2632(200004)85:2/3<209::AID-IROH209>3.0.CO;2-5
Manca MM, Portogallo M, Brown ME, 2007a. Shifts in phenology of Bythotrephes longimanus and its modern success in Lake Maggiore as a result of changes in climate and trophy. J Plankton Res 29:515-525. DOI: https://doi.org/10.1093/plankt/fbm033
Manca M, Visconti A, de Bernardi R, 2008. Lo zooplancton del Lago Maggiore nel quinquennio 2003-2007: tendenze evolutive ed eccezioni alla luce dei cambiamenti globali. Biologia Ambientale 22:64-72.
Manca M, Torretta B, Comoli P, Amsinck SL, Jeppesen E, 2007. Major changes in trophic dynamics in large, deep sub-alpine Lake Maggiore from 1940s to 2002: A high resolution comparative palaeo-neolimnological study. Freshwater Biol 52:2256-2269. DOI: https://doi.org/10.1111/j.1365-2427.2007.01827.x
Manca M, Beltrami M, Comoli P, Cavicchioni N, de Bernardi, 1998. Indagini sullo zooplancton. In: Istituto Italiano di Idrobiologia - CNR. Ricerche sull'evoluzione del Lago Maggiore. Indagini limnologiche. Campagna 1997. Relazione finale per il quinquennio. Commissione Internazionale per la Protezione delle Acque Italo-Svizzere; 52 pp.
Manca M, Calderoni A, Mosello R, 1992. Limnological research in Lago Maggiore: studies on hydrochemistry and plankton. Mem Ist ital Idrobiol 50: 171-200.
Margaritora FG, 1985. Fauna d’Italia. Cladocera. Calderini, Bologna; 399 pp.
Martin JL, Santi I, Pitta P, John U, Gypens N, 2022. Towards quantitative metabarcoding of eukaryotic plankton: an approach to improve 18S rRNA gene copy number bias. Metabarcoding Metagenomics 6:e85794. DOI: https://doi.org/10.3897/mbmg.6.85794
Martin M, 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17:10-12. DOI: https://doi.org/10.14806/ej.17.1.200
Martínez A, Eckert EM, Artois T, Careddu G, Casu M, Curini-Galletti M, et al, 2020. Human access impacts biodiversity of microscopic animals in sandy beaches. Commun Biol 3:1-9. DOI: https://doi.org/10.1038/s42003-020-0912-6
McManus GB, Katz LA, 2009. Molecular and morphological methods for identifying plankton: what makes a successful marriage? J Plankton Res 31:1119-1129. DOI: https://doi.org/10.1093/plankt/fbp061
Morpurgo M, Schuchert P, Vorhauser S, Alber R, 2021. Occurrence of two distinct lineages of the freshwater jellyfish Craspedacusta sowerbii (Hydrozoa: Limnomedusae) in Italy. J Limnol 80:1974. DOI: https://doi.org/10.4081/jlimnol.2020.1974
Mosello R, Bertoni R, Guilizzoni P, 2010. Limnological and palaeolimnological research on Lake Maggiore as a contribution to transboundary cooperation between Italy and Switzerland transboundary lakes and rivers, p. 160-167. In: Ganoulis J, Aureli A, Fried J (eds), Transboundary water resources management. A multidisciplinary approach. Weinheim: Wiley.
Obertegger U, Manca M, 2011. Response of rotifer functional groups to changing trophic state and crustacean community. J Limnol 70:231-238. DOI: https://doi.org/10.4081/jlimnol.2011.231
Obertegger U, Flaim G, Fontaneto D, 2014. Cryptic diversity within the rotifer Polyarthra dolichoptera along an altitudinal gradient. Freshwater Biol 59:2413-2427. DOI: https://doi.org/10.1111/fwb.12447
Pace ML, 1986. An empirical analysis of zooplankton community size structure across lake trophic gradients. Limnol Oceanogr 31:45-55. DOI: https://doi.org/10.4319/lo.1986.31.1.0045
Pappalardo P, Collins AG, Pagenkopp Lohan KM, Hanson KM, Truskey SB, Jaeckle W, et al., 2021. The role of taxonomic expertise in interpretation of metabarcoding studies. ICES J Mar Sci 78:3397-3410. DOI: https://doi.org/10.1093/icesjms/fsab082
Piñol J, Senar MA, Symondson WOC, 2019. The choice of universal primers and the characteristics of the species mixture determine when DNA metabarcoding can be quantitative. Mol Ecol 28:407-419. DOI: https://doi.org/10.1111/mec.14776
R Core Team, 2022. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Available from: https://www.R-project.org/
Ramazzotti G, 1962. Ritrovamento della medusa dulciacquicola Craspedacusta sowerbyi nella regione del Lago Maggiore. Mem Ist ital Idrobiol 15:175-181.
Ravera O, 1953. Gli stadi di sviluppo dei Copepodi pelagici del Lago Maggiore. Mem Ist ital Idrobiol 7:129-150.
Rey A, Corell J, Rodriguez-Ezpeleta N, 2020. Metabarcoding to study zooplankton diversity, p. 252-263. In: Teodosio MA, Branco Barbosa AN (eds) Zooplankton Ecology. Boca Raton, CRC Press. DOI: https://doi.org/10.1201/9781351021821-14
Santoferrara LF, 2019. Current practice in plankton metabarcoding: optimization and error management. J Plankton Res 41:571-582. DOI: https://doi.org/10.1093/plankt/fbz041
Schlick-Steiner BC, Steiner FM, Seifert B, Stauffer C, Christian E, Crozier RH, 2010. Integrative taxonomy: a multisource approach to exploring biodiversity. Ann Rev Entomol 55:421-438. DOI: https://doi.org/10.1146/annurev-ento-112408-085432
Simboura N, Panayotidis P, Papathanassiou E, 2005. A synthesis of the biological quality elements for the implementation of the European Water Framework Directive in the Mediterranean ecoregion: The case of Saronikos Gulf. Ecol Indic 5:253-266. DOI: https://doi.org/10.1016/j.ecolind.2005.03.006
Stefani F, Leoni B, Marieni A, Garibaldi L, 2010. A new record of Craspedacusta sowerbii, Lankester 1880 (Cnidaria, Limnomedusae) in northern Italy. J Limnol 69:189. DOI: https://doi.org/10.4081/jlimnol.2010.189
Stefanni S, Stanković D, Borme D, de Olazabal A, Juretić T, Pallavicini A, Tirelli V, 2018. Multi-marker metabarcoding approach to study mesozooplankton at basin scale. Sci Rep 8:12085. DOI: https://doi.org/10.1038/s41598-018-30157-7
Vakkilainen K, Kairesalo T, Hietala J, Balayla DM, Bécares E, Van De Bund WJ, et al., 2004. Response of zooplankton to nutrient enrichment and fish in shallow lakes: A pan-European mesocosm experiment. Freshwater Biol 49:1619-1632. DOI: https://doi.org/10.1111/j.1365-2427.2004.01300.x
Visconti A, Manca M, 2010. The invasive appearance of Eudiaptomus gracilis (G.O. Sars 1863) in Lago Maggiore. J Limnol 69:353-357. DOI: https://doi.org/10.4081/jlimnol.2010.353
Visconti A, Manca M, de Bernardi R, 2008. Eutrophication-like response to climate warming: An analysis of Lago Maggiore (N. Italy) zooplankton in contrasting years. J Limnol 67:87-92. DOI: https://doi.org/10.4081/jlimnol.2008.87
Wagner C, Adrian R, 2011. Consequences of changes in thermal regime for plankton diversity and trait composition in a polymictic lake: a matter of temporal scale. Freshwater Biol 56:1949-1961. DOI: https://doi.org/10.1111/j.1365-2427.2011.02623.x
Yang J, Zhang X, 2020. eDNA metabarcoding in zooplankton improves the ecological status assessment of aquatic ecosystems. Environ Int 134:105230. DOI: https://doi.org/10.1016/j.envint.2019.105230

Supporting Agencies

CIPAIS, Progetti@CNR SOS Acque
Giuseppe Garlasché, National Research Council, Water Research Institute (CNR-IRSA), Verbania Pallanza

Département de Biologie Chimie et Géographie, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, Canada

Ester M. Eckert, National Research Council, Water Research Institute (CNR-IRSA), Verbania Pallanza

National Biodiversity Future Center (NBFC), 90133 Palermo, Italy

Diego Fontaneto, National Research Council, Water Research Institute (CNR-IRSA), Verbania Pallanza

National Biodiversity Future Center (NBFC), 90133 Palermo, Italy

How to Cite

Garlasché, Giuseppe, Giulia Borgomaneiro, Roberta Piscia, Marina Manca, Ester M. Eckert, and Diego Fontaneto. 2023. “Metabarcoding to Monitor the Crustacean Zooplankton of a Lake Improves When Using a Reference DNA Library from Local Samples”. Journal of Limnology 82 (1). https://doi.org/10.4081/jlimnol.2023.2087.